Blog Post 2

This blog post explores how COVID-19 has spread in South America. Following this initial exploration, a deeper analysis of the region’s hardest hittest country, Brazil, observes how the virus has impacted different areas of the nation.

Lachlan Moody 27809951 (Monash University)https://www.monash.edu/
09-16-2020

Brazil has unfortunately become one of the major epicenters of the COVID19 pandemic in the world, with the global virus “devastating” the country both economically and on a humanitarian level. This outcome has been blamed on the country’s inaction and “institutional paralysis”, placed squarely on the head of president Jair Bolsonaro(Political Economy and Development 2020).

This blog post will analyse just how poorly Brazil has performed relative to its regional South American neighbours. Once this has been established, the spread of the virus within the country will be mapped out to determine where things got out of control.

Data Description

Several different data sets have been used to explore this topic.

For the first data story, which relates to the spread of COVID19 in South America, the tidycovid19(Gassen 2020) package was utilised. This package contains information on COVID19 at the country level for each day from the 31st of December up until the current day, collected and collated from various sources. For a detailed breakdown of this package and the variables included in the data sets, please see Blog Post 1.

While this data is very useful for comparing the situation between countries, additional information was required to examine the internal situation within Brazil for the second data story. To this end, three data sets provided within the wcota/covid19br(Cota 2020) GitHub repository were used, the information for which was downloaded from Brazil’s Ministry of Health(n.d.) and translated into English. The three data sets used were:

cases-brazil-cities-time.csv

709,775 records for COVID19 case data for Brazil by city and date across the following 17 variables:

cities_info.csv

Data on 5,570 cities in Brazil across the following 8 variables:

gps_cities.csv

Location data on 5,570 cities in Brazil across the following 5 variables:

For the purposes of this analysis, the three data sets above were joined using the ibge/ibgeID to link the observations contained within each.

Data Story 1: Spread of COVID19 in South America

Data Story 2: Spread of COVID19 in Brazil

Cota, Wesley. 2020. “Monitoring the Number of COVID-19 Cases and Deaths in Brazil at Municipal and Federative Units Level.” SciELOPreprints:362, May. https://doi.org/10.1590/scielopreprints.362.

Gassen, Joachim. 2020. Tidycovid19: Download, Tidy and Visualize Covid-19 Related Data.

Political Economy, Alfredo Saad Filho Professor of, and International Development. 2020. “Coronavirus: How Brazil Became the Second Worst Affected Country in the World.” The Conversation. https://theconversation.com/coronavirus-how-brazil-became-the-second-worst-affected-country-in-the-world-141102.

n.d. Coronavírus Brasil. https://covid.saude.gov.br/.